Yang on Moving Averages

Walther · Apr 28, 2003

Quote from EliteThink:

[I have short term trend following system that makes 1 mil on the cash from '96-'01 but only makes 300k in the futures for the same amount of time.

What kind of futures do you trade and what is your system based on, how many filters( components ) and such ? Nothing too specific just outline, please.
I am ( beside option writting ) daytrader , but I would like to start working on swing system (trend following ) for indexes.
Thanks,
Walter

EliteThink · Apr 28, 2003

I mainly trade the sp and nd. Most of my systems only have two consequential parameters but the one I was referring to only has one if you simply use the entry to reverse. TradingSystemDesign.com under 'systems' if you want it.

How do you structure your option writing methodology?

Good trading.

swoop[TR] · Apr 28, 2003

1 word: drawdown.

Walther · Apr 28, 2003

Quote from EliteThink:

[. TradingSystemDesign.com under 'systems' if you want it.

Page did not work trough link.

How do you structure your option writing methodology?
I write Bonds options only, rules are :
1/ I wait when there is a reversal due ( cycle and geometry determined )
2/ Delta less then 20
3/Less then 20 days to expiration
4/Get out when premium collected doubles.
Walter

Good trading. [/B]

EliteThink · Apr 28, 2003

Quote from Walther:

I just checked the site and it is up and running, please try it again.

Interesting methodology. Looks like you are only selling one leg and have a premium stop. Looks viable, good for you. I do quite a few strangles but use underlying price for the exit.

Walther · Apr 29, 2003

Quote from EliteThink:

I just checked the site and it is up and running, please try it again.

Interesting methodology. Looks like you are only selling one leg and have a premium stop. Looks viable, good for you. I do quite a few strangles but use underlying price for the exit.

Yes I sell only one leg at the time but sometimes I have both legs on.
I have tried stop loss exit when option went into money, but it was more costly and i did not usually get chance to sell higher strike again in the same contract.
Walter

hwaxen · May 3, 2003

Another way to look at moving averages is from a post I did several weeks ago and that is comparing the time spent above to the time spent below a significant moving average. A significant moving average would be a 50 or 200 day.

Since the time involved here are either 50 or 200 day averages this is a longer term tool.

As the average time above a significant moving average outpaces the average time spent below, this points to a change in the longer term trend.

We have seen this recently in the 50 day average as the average time below the 50 was dropping while the average time above the 50 was flat to increasing.

man · May 5, 2003

hwaxen
I like the basic idea. though I guess it suffers the problem of being late in the trend. did you do testing on this?

peace

harrytrader · May 24, 2003

SQRT((261*(2002-1970))-1)*1*100*3 = +/- 27415 %

this is just a very rough order estimation of performance for buying or selling randomly between 1970 and 2002 that is to say a person could make a POSITIVE performance of an order of 27415% and an other a NEGATIVE performance of - 27415% and not be more or less competant than the first one whose people could think he has a financial genious touch whereas it could be just by chance

. And since I used an understimated law by taking a random normal law this order should be much greater in reality and reach 50000 or 100000% so that the numbers below are not significant statistically and that's what economists have already said

.

This is a classical flaw in Stock Market similar to the gambler's flaw in casino gambling. The more frequent the trading and the more expanded the total time period the more big the cumulative percentage. As an other consequence and for exactly the same reason it is also a flaw comparing 1 or 2 days moving average results with 200 days moving average because the law of variation is not the same and is more volatile by definition for short than long MA.

This is kind of myth like the martingale for gamblers keep people abreast of finding the holy grail for making eally rich without any effort ... and real edge

. Of course counting on chance it's always possible but it is also possible to get ruined as rapidly : -50000% could be as probable as -50000% cumulating all the years.

The vendors of trading systems use the same kind of trick for showing superformance. In fact many if not all trading system testers are flawed with that kind of presentation tool when it is the main if not single possibility of visualising performance. This is only "apparent" performance not true that is to say comparable performance.

Quote from Avalanche:

Astrikos is free this week so I cut and pasted something from there here that should interest many.

Astrikos hardly ever has a free week, so it's definitely worth checking out. To get in the rest of the week the username is free and the password is pass.

Cheers.

By Rainsford Yang
Wednesday, April 23rd 2003 9:00pm ET

There's been a lot of press recently concerning the fact that the S&P500 has closed above its 200-day moving average, which sounds a lot more impressive than it really is. We've done extensive research on moving averages, and as far as the major stock market averages are concerned, a close above the 200-day moving average is absolutely meaningless. In fact, simple moving averages in general, except for the very short-term ones, should be disregarded in my opinion. Our studies clearly show that the best performing moving average (the 1-day average) isn't an average at all - it's simply today's close. If it's higher than yesterday's, the trend is up. If it's lower, the trend is down. This most basic of 'strategies' blew away all longer-term moving average strategies by a mile, as you'll see by the results of the studies below. And you can bet these results won't make it to the mainstream media anytime soon. No one would believe it.

We're going to review three typical strategies for employing moving averages - the 'penetration', the 'crossover' and the 'slope' - beginning with a brief explanation of each strategy, and followed by a short list of the moving averages that produced the best returns in terms of buying and selling the S&P500. In every case, simple moving averages were used, and performance figures are based on the daily S&P500 close beginning in 1970 and finishing at the present.

Moving Average Penetration
This strategy goes long the market when the S&P500 closes above its X-period moving average (upside penetration), and goes short the market when the S&P closes below its X-period moving average (downside penetration).

Best performing moving averages:
2-day moving average: +54,859%
3-day moving average: +46,038%
4-day moving average: +10,371%

Other "popular" moving averages:
10-day moving average: +974%
200-day moving average: +601%
50-day moving average: +370%

Clearly, the shorter the moving average, the more effective the 'penetration' strategy. Using a 2-day average would have returned nearly 55,000% since 1970, meaning $10,000 would have turned into a cool $5.5 million. Approximately 40% of the trades were winners, and the average winner was 1 1/2 times the average loser. Of course, with nearly 4,000 trades in 33 years, you'd be establishing a new position roughly every other day, making you very popular with your broker. The oft-mentioned 200-day moving average penetration, that gets more press than any other moving average setup, underperformed buy & hold significantly. Why does it still warrant such attention?

Moving Average Crossover
This strategy goes long the market when an X-period moving average crosses above a Y-period moving average, and goes short the market when an X-period moving average crosses below a Y-period moving average.

Best performing combinations:
60/190 moving averages: +798%
2/200 moving averages: +792%
2/180 moving averages: +690%

Other "popular" combinations:
50/200 moving averages: +648%
60/180 moving averages: +538%
40/200 moving averages: +502%

The best performing crossover signals all occurred using a very long-term average (180 days or more) and a short-term average (anywhere from 2-60 days). I've also included some of the more popular crossovers for comparison, including the 50/200 and 60/180. However, an important point to keep in mind when it comes to all of the crossover strategies is that every single one underperformed buy & hold, most by a significant amount. Therefore, we can safely conclude that the concept of using two moving averages that cross one another to trigger buy and sell signals does not work.

Moving Average Slope
This strategy goes long the market when an X-period moving average is greater than the previous day's moving average (slope is positive), and goes short the market when an X-period moving average is less than the previous day's moving average (slope is negative).

Best performing moving averages:
1-day moving average: +54,859%
2-day moving average: +20,912%
111-day moving average: +1,250%

Other "popular" moving averages:
200-day moving average: +244%
20-day moving average: +143%
50-day moving average: +47%

All of the popular averages (20-day, 50-day, 200-day) underperformed buy & hold significantly, which suggests that looking at the slope of these averages is not beneficial in the slightest. Again, it's the very short-term averages that performed best, beginning with the 1-day (which isn't really an average at all), followed by the 2-day and then the 111-day. That last one is interesting, since there were a number of moving averages in the 110-120 day range that outperformed buy & hold. If you were thinking of including a longer-term moving average in your work, one in this range would be more beneficial than the 200-day average. You might also notice that the 1-day moving average performance is the same as the 2-day 'penetration' performance, and that's because they are the same. Think about the concept of the penetration strategy. If today's close is higher than yesterday's close, it'll also be higher than the 2-day average of today's close and yesterday's close. Similarly, if today is lower than yesterday, it'll also be lower than the 2-day average of today and yesterday. Hence, the 1-day slope and the 2-day penetration strategy trigger the exact same signals. Both simply take into account solely what happened today, and use that as the basis for what may occur tomorrow. Clearly, if you're utilizing moving averages in your trading methodology, it's most important to see what's occurring right now, as opposed to what's occurred on average over the past X amount of days. This also tends to suggest that exponential and/or weighted moving averages, which give more weight to current data and less weight to past data, would probably be more effective overall than simple moving averages. I'll examine this in greater detail in a future column.

harrytrader · May 24, 2003

Many people say that this is due to psychology. It is rather due to lack of applying knowledge. For example when I began as a quality engineer there was a dispute between two chiefs one was quality engineer in a plant and the other quality chief at the headquater. The first affirmed that he has improved the quality because statistically he said that all the products were in statistical controled zone and the other said that obviously the quality was bad and get too many complaints from clients and above all the CEO was very angry and howling like a beast (I once heard him myself

) that he was surprised that statistics was so good

. I was invited to give an arbitrage by the superchief and unhappily for the first engineer he has made a flaw when estimating his statistical zone since he overestimated by a factor of 250%

. He was even threating the other man of being incompetent whereas although he was an engineer it was him that showed incompetency. He was mocking the other and in fact he wanted to get him sacked and get his post with higher salary

. it was him who got ridiculous at the end and didn't get the promotion he wanted to stealth to an other.

Quote from harrytrader:

SQRT((261*(2002-1970))-1)*1*100*3 = +/- 27415 %

this is just a very rough order estimation of performance for buying or selling randomly between 1970 and 2002 that is to say a person could make a POSITIVE performance of an order of 27415% and an other a NEGATIVE performance of - 27415% and not be more or less competant than the first one whose people could think he has a financial genious touch whereas it could be just by chance . And since I used an understimated law by taking a random normal law this order should be much greater in reality and reach 50000 or 100000% so that the numbers below are not significant statistically and that's what economists have already said .

This is a classical flaw in Stock Market similar to the gambler's flaw in casino gambling. The more frequent the trading and the more expanded the total time period the more big the cumulative percentage. As an other consequence and for exactly the same reason it is also a flaw comparing 1 or 2 days moving average results with 200 days moving average because the law of variation is not the same and is more volatile by definition for short than long MA.

This is kind of myth like the martingale for gamblers keep people abreast of finding the holy grail for making eally rich without any effort ... and real edge . Of course counting on chance it's always possible but it is also possible to get ruined as rapidly : -50000% could be as probable as -50000% cumulating all the years.

The vendors of trading systems use the same kind of trick for showing superformance. In fact many if not all trading system testers are flawed with that kind of presentation tool when it is the main if not single possibility of visualising performance. This is only "apparent" performance not true that is to say comparable performance.